Key

2.1 Statistical survey life cycle

Our statistical life cycle model is based on the work done by Statistics New Zealand, by Statistics Sweden and by METIS.We have also attended one Statistical Open Source workshop hosted by Statistics Netherlands in 2007 on this topic.

The phases we are currently using are as follows: 1. NeedSpecify Needs, 2. Design, 3. Build, 4. Collect, 5. Process, 6. Analyse and 7. Disseminate. We also have two overarching phases 8 Quality management - evaluate and feedback and 9 Support and infrastructure.

Comparison with the Generic Statistical Process Model from 16th October v4.0 from April 2009 by the UNECE secretariat: Phase 8. Archive is covered in our model by sub-processes. The quality management part of the overarching phase Quality management/Metadata management is covered by our phase 8 Quality management - evaluate and feedback, while the metadata management part is covered in our model by sub-processes.

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2004 was the last year in the development phase for the Stabas-project.However, we are now planning an improved editor tool.

Service library for metadata systems (implemented)

The purpose of this project is was to

• Create a library of services for the master systems Vardok, Datadok, Metadb and Stabas.

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NUDB : All individually based statistics on education from completed lower secondary education to tertiary education from 1970 to the present.

Systems System for questionnaires and rules and planning information

Systems exist but are being replaced.

Adminstrative system for statistical products are all under development(implemented)

Systems exist but these will be replaced.

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2005

2006

2007

2008

Total

Senior adviser

200

300

325

230

1055

System architect

200

200

210

140

750

IT developer

150

1310

975

470

2905

Web designer

-

390

370

180

940

Total

550

2200

1880

1020

5650

Benefits:

Statistics Norway's Strategies 2007 emphasise systematic quality control of products and processes. Statistics Norway's IT-strategies 2007 emphasise that - metadata systems contribute to simplifying, improving and re-use of work processes - data that are disseminated and exchanged must in addition to an agreed structure have sufficient metadata to give them meaning - use of metadata systems are a pre-condition for the development of efficient data capture solutions according to Statistics Norway's data capture strategy.